Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Notebook Cell 2.1.3
sbs.save_checkpoint('model_checkpoint.pth')
Resuming Training
Remember, when we did this in Chapter 2 we had to set the stage, loading the data
and configuring the model, before actually loading the model. We still need to do
this, but we are now using the latest version of model configuration:
Run - Model Configuration V4
%run -i model_configuration/v4.py
Let’s double-check that we do have an untrained model:
print(model.state_dict())
Output
OrderedDict([('0.weight', tensor([[0.7645]], device='cuda:0')),
('0.bias', tensor([0.8300], device='cuda:0'))])
Good, same as before! Besides, the model configuration has created the three
elements we need to pass as arguments to instantiate our StepByStep class:
Notebook Cell 2.1.4
new_sbs = StepByStep(model, loss_fn, optimizer)
Next, let’s load the trained model back using the load_checkpoint() method and
then inspect the model’s weights:
Notebook Cell 2.1.5
new_sbs.load_checkpoint('model_checkpoint.pth')
print(model.state_dict())
200 | Chapter 2.1: Going Classy